extern/whisper.cpp
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whisper : reduce ggml_context usage

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Georgi Gerganov 2024-10-30 13:39:14 +02:00
parent 55e422109b
commit 3689d49b81
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GPG Key ID: 449E073F9DC10735
2 changed files with 16 additions and 14 deletions
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2
ggml/src/ggml.c
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@ -3853,7 +3853,7 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
} }
if (ctx == NULL) { if (ctx == NULL) {
GGML_PRINT_DEBUG("%s: no unused context found\n", __func__); GGML_LOG_ERROR("%s: ran out of contexts (max = %d)\n", __func__, GGML_MAX_CONTEXTS);
ggml_critical_section_end(); ggml_critical_section_end();

28
src/whisper.cpp
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@ -699,9 +699,9 @@ struct whisper_kv_cache {
struct ggml_tensor * k; struct ggml_tensor * k;
struct ggml_tensor * v; struct ggml_tensor * v;
struct ggml_context * ctx = nullptr;
ggml_backend_buffer_t buffer = nullptr; ggml_backend_buffer_t buffer = nullptr;
std::vector<uint8_t> ctx_buf;
}; };
struct whisper_model { struct whisper_model {
@ -941,9 +941,11 @@ static bool whisper_kv_cache_init(
const int64_t n_mem = n_text_layer*n_ctx; const int64_t n_mem = n_text_layer*n_ctx;
const int64_t n_elements = n_text_state*n_mem; const int64_t n_elements = n_text_state*n_mem;
cache.ctx_buf.resize(2*ggml_tensor_overhead());
struct ggml_init_params params = { struct ggml_init_params params = {
/*.mem_size =*/ 2*ggml_tensor_overhead(), /*.mem_size =*/ cache.ctx_buf.size(),
/*.mem_buffer =*/ nullptr, /*.mem_buffer =*/ cache.ctx_buf.data(),
/*.no_alloc =*/ true, /*.no_alloc =*/ true,
}; };
@ -953,17 +955,17 @@ static bool whisper_kv_cache_init(
cache.cells.clear(); cache.cells.clear();
cache.cells.resize(n_ctx); cache.cells.resize(n_ctx);
cache.ctx = ggml_init(params); struct ggml_context * ctx = ggml_init(params);
if (!cache.ctx) { if (!ctx) {
WHISPER_LOG_ERROR("%s: failed to allocate memory for the kv cache context\n", __func__); WHISPER_LOG_ERROR("%s: failed to allocate memory for the kv cache context\n", __func__);
return false; return false;
} }
cache.k = ggml_new_tensor_1d(cache.ctx, wtype, n_elements); cache.k = ggml_new_tensor_1d(ctx, wtype, n_elements);
cache.v = ggml_new_tensor_1d(cache.ctx, wtype, n_elements); cache.v = ggml_new_tensor_1d(ctx, wtype, n_elements);
cache.buffer = ggml_backend_alloc_ctx_tensors(cache.ctx, backend); cache.buffer = ggml_backend_alloc_ctx_tensors(ctx, backend);
if (!cache.buffer) { if (!cache.buffer) {
WHISPER_LOG_ERROR("%s: failed to allocate memory for the kv cache\n", __func__); WHISPER_LOG_ERROR("%s: failed to allocate memory for the kv cache\n", __func__);
return false; return false;
@ -971,13 +973,13 @@ static bool whisper_kv_cache_init(
ggml_backend_buffer_clear(cache.buffer, 0); ggml_backend_buffer_clear(cache.buffer, 0);
ggml_free(ctx);
return true; return true;
} }
static void whisper_kv_cache_free(struct whisper_kv_cache & cache) { static void whisper_kv_cache_free(struct whisper_kv_cache & cache) {
ggml_free(cache.ctx);
ggml_backend_buffer_free(cache.buffer); ggml_backend_buffer_free(cache.buffer);
cache.ctx = nullptr;
} }
static bool whisper_kv_cache_find_slot( static bool whisper_kv_cache_find_slot(
@ -2002,7 +2004,7 @@ static struct ggml_cgraph * whisper_build_graph_encoder(
auto & kv_pad = wstate.kv_pad; auto & kv_pad = wstate.kv_pad;
WHISPER_ASSERT(!!kv_pad.ctx); WHISPER_ASSERT(!!kv_pad.buffer);
const int n_ctx_pad = GGML_PAD(n_ctx, 256); const int n_ctx_pad = GGML_PAD(n_ctx, 256);
@ -2416,7 +2418,7 @@ static struct ggml_cgraph * whisper_build_graph_decoder(
auto & kv_self = wstate.kv_self; auto & kv_self = wstate.kv_self;
WHISPER_ASSERT(!!kv_self.ctx); WHISPER_ASSERT(!!kv_self.buffer);
const int n_ctx = kv_self.size; const int n_ctx = kv_self.size;
const int n_state = hparams.n_text_state; const int n_state = hparams.n_text_state;